Environment-Dependent Throughput Distribution Estimation Based on Bayesian Approach for mmWave Vehicular Communications
Environment-Dependent Throughput Distribution Estimation Based on Bayesian Approach for mmWave Vehicular Communications
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DOI：
10.1109/vtc2023-spring57618.2023.10200424
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Yuhi Kurebayashi;Akihito Taya;Yoshito Tobe
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文献类型：
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作者：
Yuhi Kurebayashi;Akihito Taya;Yoshito Tobe
近年来，车对车（V2V）通信不仅用于避免碰撞等安全驾驶辅助，还用于使用动态地图和远程控制的高级自动驾驶。超可靠低延迟通信 (URLLC) 对于安全相关功能是必要的，例如驾驶员辅助和自动驾驶。由于移动性高，V2V通信必须在各种通信环境中进行。然而，作为 URLLC 推动者的毫米波 (mmWave) 通信受环境影响很大，例如：地形、车辆密度等。本文提出了一种用于毫米波 V2X 通信的环境相关吞吐量估计方法。路边单元 (RSU) 收集附近车辆吞吐量的信息，并使用贝叶斯方法计算其分布模型。所提出的方法提供了一种回归方案来估计没有 RSU 的区域的吞吐量的分布模型。仿真评估验证了 beta 分布非常适合毫米波车辆通信的吞吐量，并且回归方案可以估计没有 RSU 的区域的吞吐量模型。
In recent years, vehicle-to-vehicle (V2V) communications are used not only for safe driving assistance such as collision avoidance but also for advanced autonomous driving using dynamic maps and remote control. Ultra-reliable low-latency communications (URLLC) are necessary for safety-related functions, e.g. driver assistance and autonomous driving. Due to high mobility, V2V communication must be performed in a variety of communication environments. However, millimeter wave (mmWave) communications, an enabler of URLLC, are greatly affected by the environment, e.g. the terrain, density of vehicles, etc.. This paper proposes an environment-dependent throughput estimation method for mmWave V2X communications. Roadside units (RSUs) collect information on the throughputs of their nearby vehicles and calculate their distribution model with the Bayesian approach. The proposed method provides a regression scheme to estimate distribution models of the throughput of the area without RSUs. The simulation evaluation validates that the beta distribution fits well for the throughput of mmWave vehicular communication and that the regression scheme can estimate throughput models of the area without RSUs.